Data analyses, interim reviews and design issues of longitudinal study in biomedical research

许多生物医学研究关注的是个人或群体随时间的发展。这项研究的总体目标是开发新的理论和方法来分析来自纵向研究的数据，并用于研究设计和监测。由于现有的治疗方法、生物学知识和护理标准正在迅速发展，因此对预期治疗效果的性质和大小以及某些类型的结果测量差异的临床意义可能知之甚少，因此在许多健康研究中最好采用适度模型假设的方法。第一个具体目标是进一步发展强有力的统计方法，从收集的纵向数据中量化时间趋势和变量之间的联系。临床试验设计中的伦理和经济考虑因素，以评估新疗法的疗效和可能的毒性效应，以及纵向试验期间信息流的固有顺序性质，导致人们对监测研究的分组序贯方法和提供适应性设计的研究越来越感兴趣。我们的第二个具体目标是完善用于临床试验正式审查的重复可信区间方法的发展，并为研究设计提供对可用信息的有效适应。第三个具体目标是在纵向反应、可能不完全的和大量解释变量的情况下发展回归分析方法。这是由建立疾病进展和临床结果之间的联系以及患者的生物标记物或基因表达数据的科学兴趣所推动的。研究结果将通过出版物、会议和软件分发向医学研究人员和生物统计学从业者传播，并说明其在最近的医学研究中的应用。此外，参与的学生将做好充分准备，以满足实践中对统计支持的各种需求，特别是在医疗环境中。

Many biomedical studies are concerned with the development of persons or groups over time. The broad objective of this research is to develop new theory and methods for analyzing data from longitudinal study and for study design and monitoring. Since available therapies, biological knowledge, and standard of care are rapidly evolving and thus relatively little may be known about the nature and magnitude of the expected treatment effect and about the clinical significance of certain types of differences in the outcome measure, approaches with modest model assumption are desirable in many health studies. The first specific objective is further development of robust statistical approaches to quantifying the time trend and association between variables over time from the collected longitudinal data. The ethical and economic considerations in the design of clinical trials to evaluate the efficacy and possible toxicity effects of new therapies, together with the inherent sequential nature of the information flow during the longitudinal trials, are responsible for the increasing interest in group sequential methods for monitoring the studies and for providing studies with adaptive designs. Our second specific objective is to fill out the development of the repeated confidence bands approach for formal reviews in clinical trials, and to provide study designs with efficient adaptation of the available information. The third specific objective is to develop regression analysis methods in the situations with longitudinal response, possibly incomplete, and a large number of explanatory variables. This is motivated by the scientific interest in establishing the association between disease progression and clinical outcome over time and patient's biomarker or gene expression data. The research results, illustrated with their applications to recent medical studies, will be disseminated to medical investigators and biostatistical practitioners via publications, conferences and software distribution. In addition, the students involved will be well-prepared to meet the various demands of statistical support in practice, particularly in medical settings.